

use "/Users/dbarker/Library/CloudStorage/GoogleDrive-david.c.barker1969@gmail.com/My Drive/Research/Turnout Experiment/yougov 2020 simple for POQ replication 3 18 24.dta"


* Replication code: POQ "Reducing Racial Asymmetries in the Overestimating of Voter Turnout"



*Renaming and recoding the treatment vs. control variable 

gen treatment=split_AB
tab treatment
replace treatment=treatment-1
label variable treatment "0=control (asked separately) ; 1=treatment (asked together)"

tab treatment [aw=weight]


* Creating the simplified race variable that includes and distinguishes only Black respondents from White respondents

tab race [aweight=weight]

gen blackwhite = 1 if race==2
replace blackwhite = 0 if race==1
label variable blackwhite "white=0; black=1; other=."
tab blackwhite [aw=weight]

tab treatment if blackwhite !=. [aweight=weight]
tab treatment if blackwhite==0 [aweight=0]
tab treatment if blackwhite==1 [aweight=weight]


* Creating the outcome variable 

* Step one: creating the validated turnout variable that we use, which we do by taking the validated variable we received from targetsmart and augmented it such that nonregistered respondents are counted as nonvoters.  This also enables us to observe sample loss

gen turnoutvalidnonregtononvoter =  turnoutvalidatedfromtsmart 
replace turnoutvalidnonregtononvoter = 0 if votereg>=2
replace turnoutvalidnonregtononvoter=. if turnoutvalidnonregtononvoter==.
tab turnoutvalidnonregtononvoter [aw=weight]
bysort treatment: tab turnoutvalidnonregtononvoter [aw=weight]
bysort blackwhite: tab turnoutvalidnonregtononvoter [aw=weight]

tab race if turnoutvalidnonregtononvoter!=.
tab race if turnoutvalidnonregtononvoter!=. [aw=weight]

gen tsmartvalidornotnonregtononvoter=0 if tsmartvalidatedornot==0 & turnoutvalidnonregtononvoter ==.
replace tsmartvalidornotnonregtononvoter=1 if turnoutvalidnonregtononvoter !=.

tab tsmartvalidornotnonregtononvoter if blackwhite!=. 
tab tsmartvalidornotnonregtononvoter if blackwhite!=0 
tab tsmartvalidornotnonregtononvoter if blackwhite!=1 

tab treatment tsmartvalidornotnonregtononvoter if blackwhite !=. [aweight=weight], cell 
tab treatment tsmartvalidornotnonregtononvoter if blackwhite==0 [aweight=weight], cell 
tab treatment tsmartvalidornotnonregtononvoter if blackwhite==1 [aweight=weight], cell 

ttest tsmartvalidornotnonregtononvoter, by (blackwhite)
ttest tsmartvalidornotnonregtononvoter, by (treatment)

ttest tsmartvalidornotnonregtononvoter if blackwhite !=., by (treatment) 
ttest tsmartvalidornotnonregtononvoter if blackwhite ==0, by (treatment) 
ttest tsmartvalidornotnonregtononvoter if blackwhite ==1, by (treatment) 


* Step two: creating respondents' stated turnout intention variable across both experimental groups

gen turnoutplansimpledic = 1 if q21A==1 | q21B<=2
replace turnoutplansimpledic = 0 if q21A==2 | q21B==3
tab turnoutplansimpledic [aw=weight]
tab turnoutplansimpledic if blackwhite !=. [aw=weight]
tab turnoutplansimpledic if blackwhite==0  [aw=weight]
tab turnoutplansimpledic if blackwhite==1 [aw=weight]
tab turnoutplansimpledic if turnoutvalidnonregtononvoter !=. [aweight=weight]
tab turnoutplansimpledic if turnoutvalidnonregtononvoter !=. & blackwhite==0 [aweight=weight]
tab turnoutplansimpledic if turnoutvalidnonregtononvoter !=. & blackwhite==1 [aweight=weight]
bysort treatment: tab turnoutplansimpledic if blackwhite !=. [aweight=weight]
bysort treatment: tab turnoutplansimpledic if blackwhite !=. & turnoutvalidnonregtononvoter !=. [aw=weight]
bysort treatment: tab turnoutplansimpledic if blackwhite==0 [aweight=weight]
bysort treatment: tab turnoutplansimpledic if blackwhite==0 & turnoutvalidnonregtononvoter !=. [aw=weight]
bysort treatment: tab turnoutplansimpledic if blackwhite==1 [aweight=weight]
bysort treatment: tab turnoutplansimpledic if blackwhite==1 & turnoutvalidnonregtononvoter !=. [aw=weight]

* Step three: subtracting respondents' stated turnout intentions from their validated voting behavior

gen turnoutoverorunder=turnoutplansimpledic-turnoutvalidnonregtononvoter

* Step four: replacing "underestimates" to zero, since our theory does not distinguish the rare case of underestimating from intention-validated matches.

gen turnoutoverestimated=turnoutoverorunder
replace turnoutoverestimated=0 if turnoutoverorunder==-1

tab turnoutoverestimated if blackwhite !=. [aweight=weight]
tab turnoutoverestimated if blackwhite ==0 [aweight=weight]
tab turnoutoverestimated if blackwhite ==1 [aweight=weight]


* Now create the interaction term of treatmentXblack

gen treatXblack=treatment*blackwhite

* now convert gender to "female"

gen female = gender-1

* now center the non-binary control variables (so mean=0) for most realistic interpretation

mcenter birthyr educ faminc_new


* Now estimate simple model for Figure/Table 1

cloglog turnoutoverestimated treatment blackwhite treatXblack female C_birthyr C_educ C_faminc_new [pw=weight], cluster (surveyduration)

* now convert to marginal effects:

margins, dydx (*)

prvalue, x (treatment=0 blackwhite=0 treatXblack=0)
prvalue, x (treatment=0 blackwhite=1 treatXblack=0)
prvalue, x (treatment=1 blackwhite=0 treatXblack=0)
prvalue, x (treatment=1 blackwhite=1 treatXblack=1)


* Now create the Racial Civic Consciousness variable (RCC) with a weighted index (principal component) of r's (1) sense of civic duty toward the country, (2) sense of civic duty toward racial group, and (3) racial identity consciousness

*the first variable in that index is racial identity:

gen racialidentity= 0 if q6_new_grid_1==0 | q18_4==0 
replace racialidentity= 1 if q6_new_grid_1==1 | q18_4==1
replace racialidentity= 2 if q6_new_grid_1==2 | q18_4==2
replace racialidentity= 3 if q6_new_grid_1==3 | q18_4==3
replace racialidentity= 4 if q6_new_grid_1==4 | q18_4==4
replace racialidentity= 5 if q6_new_grid_1==5 | q18_4==5
replace racialidentity= 6 if q6_new_grid_1==6 | q18_4==6
tab racialidentity
label variable racialidentity "q6_new_grid_1 & q18_4"

*The second item in the racial civic consciousness index is generic civic duty

tab q7_1
gen civicdutygeneral= q7_1 if q7_1 <=5


* The third item is civic duty as applied to race:
tab q7_3
gen civicdutyrace= q7_3 if q7_3 <=5


*now to show the alpha and the principal components analysis results
alpha racialidentity civicdutygeneral civicdutyrace if blackwhite !=. & turnoutvalidnonregtononvoter !=.
alpha racialidentity civicdutygeneral civicdutyrace if blackwhite==0 & turnoutvalidnonregtononvoter !=.
alpha racialidentity civicdutygeneral civicdutyrace if blackwhite==1 & turnoutvalidnonregtononvoter !=.

pca racialidentity civicdutygeneral civicdutyrace if blackwhite==0 & turnoutvalidnonregtononvoter !=.
pca racialidentity civicdutygeneral civicdutyrace if blackwhite==1 & turnoutvalidnonregtononvoter !=.
pca racialidentity civicdutygeneral civicdutyrace if blackwhite !=. & turnoutvalidnonregtononvoter !=.

predict RCCpca301
label variable RCCpca301 "RCC pca index: identityrace dutyrace civicdutygeneral"
sum RCCpca301
replace RCCpca301= RCCpca301+2.854426
sum RCCpca301
replace RCCpca301= RCCpca301 /4.865268
sum RCCpca301
replace RCCpca301= 0 if RCCpca301 <=.0001

sum RCCpca301 if blackwhite !=. & turnoutvalidnonregtononvoter !=. [aw=weight]
sum RCCpca301 if blackwhite==0 & turnoutvalidnonregtononvoter !=. [aw=weight]
sum RCCpca301 if blackwhite==1 & turnoutvalidnonregtononvoter !=. [aw=weight]

* now trichotomizing RCCpca301

gen RCCpca3thirds = 0 if RCCpca301 <=.333
replace RCCpca3thirds = .5 if RCCpca301 >=.3331 & RCCpca301 <=.666
replace RCCpca3thirds = 1 if RCCpca301 >=.6661
replace RCCpca3thirds=. if RCCpca301==.

sum RCCpca3thirds if blackwhite !=. & turnoutvalidnonregtononvoter !=. [aw=weight]
sum RCCpca3thirds if blackwhite==0 & turnoutvalidnonregtononvoter !=. [aw=weight]
sum RCCpca3thirds if blackwhite==1 & turnoutvalidnonregtononvoter !=. [aw=weight]

*Now create interaction terms that multiply this variable by (a) treatment and (b) blackvswhite

gen treatXRCCpca3thirds=treatment*RCCpca3thirds
gen blackXRCCpca3thirds=blackwhite*RCCpca3thirds

* Now create the Campaign Indifference variable by (1) combining each of the candidate and party attitude items into a single scale for each (because they were asked with multiple questions), (2) differencing the resulting candidate scales and party scales, (2) folding them, (3) summing them, (4) flipping the variable that results, and (5) trichotomizing it to boost power. 

*The candidate attitude variables are q14, q14a, q14b & q14_new (Trump) and q15, q15a, q15b & q15_new (Biden)
*The party attitude variables are q16, q16a, q16b & q16_new (Democratic Party) and q17, q17a, q17v & q17_new (Republican Party)

gen trumpattitudescombined=1 if q14_new==1 | q14b==3
replace trumpattitudescombined=2 if q14_new==2 | q14b==2
replace trumpattitudescombined=3 if q14_new==3 | q14b==1
replace trumpattitudescombined=4 if q14_new==4 | q14==2
 replace trumpattitudescombined=5 if q14_new==5 | q14a==1
replace trumpattitudescombined=6 if q14_new==6 | q14a==2
replace trumpattitudescombined=7 if q14_new==7 | q14a==3
gen bidenattitudescombined=1 if q15_new==1 | q15b==3
replace bidenattitudescombined=2 if q15_new==2 | q15b==2
replace bidenattitudescombined=3 if q15_new==3 | q15b==1
replace bidenattitudescombined=4 if q15_new==4 | q15==2
 replace bidenattitudescombined=5 if q15_new==5 | q15a==1
replace bidenattitudescombined=6 if q15_new==6 | q15a==2
replace bidenattitudescombined=7 if q15_new==7 | q15a==3
gen demoattitudescombined=1 if q16_new==1 | q16b==3
replace demoattitudescombined=2 if q16_new==2 | q16b==2
replace demoattitudescombined=3 if q16_new==3 | q16b==1
replace demoattitudescombined=4 if q16_new==4 | q16==2
 replace demoattitudescombined=5 if q16_new==5 | q16a==1
replace demoattitudescombined=6 if q16_new==6 | q16a==2
replace demoattitudescombined=7 if q16_new==7 | q16a==3
gen gopattitudescombined=1 if q17_new==1 | q17b==3
replace gopattitudescombined=2 if q17_new==2 | q17b==2
replace gopattitudescombined=3 if q17_new==3 | q17b==1
replace gopattitudescombined=4 if q17_new==4 | q17==2
 replace gopattitudescombined=5 if q17_new==5 | q17a==1
replace gopattitudescombined=6 if q17_new==6 | q17a==2
replace gopattitudescombined=7 if q17_new==7 | q17a==3
gen dem_gopattitudes= demoattitudescombined-gopattitudescombined
gen biden_trumpattitudes= bidenattitudescombined-trumpattitudescombined

gen dem_gopfold= abs(dem_gopattitudes)
gen biden_trumpfold= abs(biden_trumpattitudes)

pca dem_gopfold biden_trumpfold 
predict CI
label variable CI "cand and party differences folded summed & flipped"
replace CI =CI*-1
replace CI =CI+1

gen CI01= CI +.465901
sum CI01
replace CI01= CI01 / 3.791456
sum CI01
replace CI01= 0 if CI01 <=.0001
sum CI01
gen CI01thirds = 0 if CI01 <=.333
replace CI01thirds = .5 if CI01 >=.3331 & CI01 <=.666
replace CI01thirds = 1 if CI01 >=.6661
replace CI01thirds=. if CI01==.

sum CI01thirds if blackwhite !=. & turnoutvalidnonregtononvoter !=. [aw=weight]
sum CI01thirds if blackwhite==0 & turnoutvalidnonregtononvoter !=. [aw=weight]
sum CI01thirds if blackwhite==1 & turnoutvalidnonregtononvoter !=. [aw=weight]

ttest CI01thirds if turnoutvalidnonregtononvoter!=., by (blackwhite)

tab RCCpca3thirds CI01thirds if blackwhite !=. [aw=weight], cell
tab RCCpca3thirds CI01thirds if blackwhite==0 [aw=weight], cell
tab RCCpca3thirds CI01thirds if blackwhite==1 [aw=weight], cell

* Now create all remaining interaction terms

gen treatXCIthirds=treatment*CI01thirds
gen blackXCIthirds = blackwhite*CI01thirds
gen RCCXCIthirds01 = RCCpca3thirds*CI01thirds
gen blackXRCCXCIthirds= blackwhite * RCCpca3thirds * CI01thirds
gen treatXRCCXCIthirds= treatment * RCCpca3thirds * CI01thirds
gen treatXblackXRCCthirds=treatment*blackwhite*RCCpca3thirds
gen treatXblackXCIthirds=treatment*blackwhite*CI01thirds
gen treatXblackXRCCXCIthrds=treatment*blackwhite*RCCpca3thirds*CI01thirds



* Now estimate model for Figure/Table 2 and convert the complementary log log coefficients to marginal effects

cloglog turnoutoverestimated blackwhite RCCpca3thirds CI01thirds blackXRCCpca3thirds blackXCIthirds RCCXCIthirds01 blackXRCCXCIthirds treatment treatXblack treatXRCCpca3thirds treatXblackXRCCthirds treatXCIthirds treatXblackXCIthirds treatXRCCXCIthirds treatXblackXRCCXCIthrds female C_birthyr C_educ C_faminc_new [pw=weight], cluster (surveyduration)

margins, dydx (*)


*Now reveal the predicted probabilities for the various combinations of treatment, blackvswhite, RCC and CI at low, medium and high levels

* First, pr black overestimating at different levels of RCC and CI

* control black, low RCC, low CI
prvalue, x (blackwhite=1 RCCpca3thirds=0 CI01thirds=0 blackXRCCpca3thirds=0 blackXCIthirds=0 RCCXCIthirds01=0 blackXRCCXCIthirds=0 treatment=0 treatXblack=0 treatXRCCpca3thirds=0 treatXblackXRCCthirds=0 treatXCIthirds=0 treatXblackXCIthirds=0 treatXRCCXCIthirds=0 treatXblackXRCCXCIthrds=0) 
* now treatment, black, low RCC, low CI 
prvalue, x (blackwhite=1 RCCpca3thirds=0 CI01thirds=0 blackXRCCpca3thirds=0 blackXCIthirds=0 RCCXCIthirds01=0 blackXRCCXCIthirds=0 treatment=1 treatXblack=1 treatXRCCpca3thirds=0 treatXblackXRCCthirds=0 treatXCIthirds=0 treatXblackXCIthirds=0 treatXRCCXCIthirds=0 treatXblackXRCCXCIthrds=0) 
* now control, black, mid RCC, mid CI 
prvalue, x (blackwhite=1 RCCpca3thirds=.5 CI01thirds=.5 blackXRCCpca3thirds=.5 blackXCIthirds=.5 RCCXCIthirds01=.25 blackXRCCXCIthirds=.25 treatment=0 treatXblack=0 treatXRCCpca3thirds=0 treatXblackXRCCthirds=0 treatXCIthirds=0 treatXblackXCIthirds=0 treatXRCCXCIthirds=0 treatXblackXRCCXCIthrds=0) 
* ditto treatment group
prvalue, x (blackwhite=1 RCCpca3thirds=.5 CI01thirds=.5 blackXRCCpca3thirds=.5 blackXCIthirds=.5 RCCXCIthirds01=.25 blackXRCCXCIthirds=.25 treatment=1 treatXblack=1 treatXRCCpca3thirds=.5 treatXblackXRCCthirds=.5 treatXCIthirds=.5 treatXblackXCIthirds=.5 treatXRCCXCIthirds=.25 treatXblackXRCCXCIthrds=.25) 
* now control hi RCC hi CI
prvalue, x (blackwhite=1 RCCpca3thirds=1 CI01thirds=1 blackXRCCpca3thirds=1 blackXCIthirds=1 RCCXCIthirds01=1 blackXRCCXCIthirds=1 treatment=0 treatXblack=0 treatXRCCpca3thirds=0 treatXblackXRCCthirds=0 treatXCIthirds=0 treatXblackXCIthirds=0 treatXRCCXCIthirds=0 treatXblackXRCCXCIthrds=0) 
* ditto treatment group
prvalue, x (blackwhite=1 RCCpca3thirds=1 CI01thirds=1 blackXRCCpca3thirds=1 blackXCIthirds=1 RCCXCIthirds01=1 blackXRCCXCIthirds=1 treatment=1 treatXblack=1 treatXRCCpca3thirds=1 treatXblackXRCCthirds=1 treatXCIthirds=1 treatXblackXCIthirds=1 treatXRCCXCIthirds=1 treatXblackXRCCXCIthrds=1) 
* now control hi RCC mid CI
prvalue, x (blackwhite=1 RCCpca3thirds=1 CI01thirds=.5 blackXRCCpca3thirds=1 blackXCIthirds=.5 RCCXCIthirds01=.5 blackXRCCXCIthirds=.5 treatment=0 treatXblack=0 treatXRCCpca3thirds=0 treatXblackXRCCthirds=0 treatXCIthirds=0 treatXblackXCIthirds=0 treatXRCCXCIthirds=0 treatXblackXRCCXCIthrds=0) 
* ditto treatment group
prvalue, x (blackwhite=1 RCCpca3thirds=1 CI01thirds=.5 blackXRCCpca3thirds=1 blackXCIthirds=.5 RCCXCIthirds01=.5 blackXRCCXCIthirds=.5 treatment=1 treatXblack=1 treatXRCCpca3thirds=1 treatXblackXRCCthirds=1 treatXCIthirds=.5 treatXblackXCIthirds=.5 treatXRCCXCIthirds=.5 treatXblackXRCCXCIthrds=.5) 
* now control mid RCC hi CI
prvalue, x (blackwhite=1 RCCpca3thirds=.5 CI01thirds=1 blackXRCCpca3thirds=.5 blackXCIthirds=1 RCCXCIthirds01=.5 blackXRCCXCIthirds=.5 treatment=0 treatXblack=0 treatXRCCpca3thirds=0 treatXblackXRCCthirds=0 treatXCIthirds=0 treatXblackXCIthirds=0 treatXRCCXCIthirds=0 treatXblackXRCCXCIthrds=0) 
* ditto treatment group
prvalue, x (blackwhite=1 RCCpca3thirds=.5 CI01thirds=1 blackXRCCpca3thirds=.5 blackXCIthirds=1 RCCXCIthirds01=.5 blackXRCCXCIthirds=.5 treatment=1 treatXblack=1 treatXRCCpca3thirds=.5 treatXblackXRCCthirds=.5 treatXCIthirds=1 treatXblackXCIthirds=1 treatXRCCXCIthirds=.5 treatXblackXRCCXCIthrds=.5) 
* now control low RCC hi CI
prvalue, x (blackwhite=1 RCCpca3thirds=0 CI01thirds=1 blackXRCCpca3thirds=0 blackXCIthirds=1 RCCXCIthirds01=0 blackXRCCXCIthirds=0 treatment=0 treatXblack=0 treatXRCCpca3thirds=0 treatXblackXRCCthirds=0 treatXCIthirds=0 treatXblackXCIthirds=0 treatXRCCXCIthirds=0 treatXblackXRCCXCIthrds=0) 
* ditto treatment group
prvalue, x (blackwhite=1 RCCpca3thirds=0 CI01thirds=1 blackXRCCpca3thirds=0 blackXCIthirds=1 RCCXCIthirds01=0 blackXRCCXCIthirds=0 treatment=1 treatXblack=1 treatXRCCpca3thirds=0 treatXblackXRCCthirds=0 treatXCIthirds=1 treatXblackXCIthirds=1 treatXRCCXCIthirds=0 treatXblackXRCCXCIthrds=0) 
* now control Hi RCC low CI
prvalue, x (blackwhite=1 RCCpca3thirds=1 CI01thirds=0 blackXRCCpca3thirds=1 blackXCIthirds=0 RCCXCIthirds01=0 blackXRCCXCIthirds=0 treatment=0 treatXblack=0 treatXRCCpca3thirds=0 treatXblackXRCCthirds=0 treatXCIthirds=0 treatXblackXCIthirds=0 treatXRCCXCIthirds=0 treatXblackXRCCXCIthrds=0) 
* ditto treatment group
prvalue, x (blackwhite=1 RCCpca3thirds=1 CI01thirds=0 blackXRCCpca3thirds=1 blackXCIthirds=0 RCCXCIthirds01=0 blackXRCCXCIthirds=0 treatment=1 treatXblack=1 treatXRCCpca3thirds=1 treatXblackXRCCthirds=1 treatXCIthirds=0 treatXblackXCIthirds=0 treatXRCCXCIthirds=0 treatXblackXRCCXCIthrds=0)

 * treatment effects on black overestimating:
* Both Low=
* Both Mid=
* Low RCC Hi CI=
* Hi RCC Low CI=
* Mid RCC Hi CI=
* Hi RCC mid CI= 
* Both High=


*Next: pr white overestimating at different levels of RCC and CI

* control, low RCC, low CI
prvalue, x (blackwhite=0 RCCpca3thirds=0 CI01thirds=0 blackXRCCpca3thirds=0 blackXCIthirds=0 RCCXCIthirds01=0 blackXRCCXCIthirds=0 treatment=0 treatXblack=0 treatXRCCpca3thirds=0 treatXblackXRCCthirds=0 treatXCIthirds=0 treatXblackXCIthirds=0 treatXRCCXCIthirds=0 treatXblackXRCCXCIthrds=0) 
* now treatment, low RCC, low CI 
prvalue, x (blackwhite=0 RCCpca3thirds=0 CI01thirds=0 blackXRCCpca3thirds=0 blackXCIthirds=0 RCCXCIthirds01=0 blackXRCCXCIthirds=0 treatment=1 treatXblack=0 treatXRCCpca3thirds=0 treatXblackXRCCthirds=0 treatXCIthirds=0 treatXblackXCIthirds=0 treatXRCCXCIthirds=0 treatXblackXRCCXCIthrds=0) 
* now control, mid RCC, mid CI 
prvalue, x (blackwhite=0 RCCpca3thirds=.5 CI01thirds=.5 blackXRCCpca3thirds=0 blackXCIthirds=0 RCCXCIthirds01=.25 blackXRCCXCIthirds=0 treatment=0 treatXblack=0 treatXRCCpca3thirds=0 treatXblackXRCCthirds=0 treatXCIthirds=0 treatXblackXCIthirds=0 treatXRCCXCIthirds=0 treatXblackXRCCXCIthrds=0) 
* ditto treatment group
prvalue, x (blackwhite=0 RCCpca3thirds=.5 CI01thirds=.5 blackXRCCpca3thirds=0 blackXCIthirds=0 RCCXCIthirds01=.25 blackXRCCXCIthirds=0 treatment=1 treatXblack=0 treatXRCCpca3thirds=.5 treatXblackXRCCthirds=0 treatXCIthirds=.5 treatXblackXCIthirds=0 treatXRCCXCIthirds=.25 treatXblackXRCCXCIthrds=0) 
* now control hi RCC hi CI
prvalue, x (blackwhite=0 RCCpca3thirds=1 CI01thirds=1 blackXRCCpca3thirds=0 blackXCIthirds=0 RCCXCIthirds01=1 blackXRCCXCIthirds=0 treatment=0 treatXblack=0 treatXRCCpca3thirds=0 treatXblackXRCCthirds=0 treatXCIthirds=0 treatXblackXCIthirds=0 treatXRCCXCIthirds=0 treatXblackXRCCXCIthrds=0) 
* ditto treatment group
prvalue, x (blackwhite=0 RCCpca3thirds=1 CI01thirds=1 blackXRCCpca3thirds=0 blackXCIthirds=0 RCCXCIthirds01=1 blackXRCCXCIthirds=0 treatment=1 treatXblack=0 treatXRCCpca3thirds=1 treatXblackXRCCthirds=0 treatXCIthirds=1 treatXblackXCIthirds=0 treatXRCCXCIthirds=1 treatXblackXRCCXCIthrds=0) 
* now control hi RCC mid CI
prvalue, x (blackwhite=0 RCCpca3thirds=1 CI01thirds=.5 blackXRCCpca3thirds=0 blackXCIthirds=0 RCCXCIthirds01=.5 blackXRCCXCIthirds=0 treatment=0 treatXblack=0 treatXRCCpca3thirds=0 treatXblackXRCCthirds=0 treatXCIthirds=0 treatXblackXCIthirds=0 treatXRCCXCIthirds=0 treatXblackXRCCXCIthrds=0) 
* ditto treatment group
prvalue, x (blackwhite=0 RCCpca3thirds=1 CI01thirds=.5 blackXRCCpca3thirds=0 blackXCIthirds=0 RCCXCIthirds01=.5 blackXRCCXCIthirds=0 treatment=1 treatXblack=0 treatXRCCpca3thirds=1 treatXblackXRCCthirds=0 treatXCIthirds=.5 treatXblackXCIthirds=0 treatXRCCXCIthirds=.5 treatXblackXRCCXCIthrds=0) 
* now control mid RCC hi CI
prvalue, x (blackwhite=0 RCCpca3thirds=.5 CI01thirds=1 blackXRCCpca3thirds=0 blackXCIthirds=0 RCCXCIthirds01=.5 blackXRCCXCIthirds=0 treatment=0 treatXblack=0 treatXRCCpca3thirds=0 treatXblackXRCCthirds=0 treatXCIthirds=0 treatXblackXCIthirds=0 treatXRCCXCIthirds=0 treatXblackXRCCXCIthrds=0) 
* ditto treatment group
prvalue, x (blackwhite=0 RCCpca3thirds=.5 CI01thirds=1 blackXRCCpca3thirds=0 blackXCIthirds=0 RCCXCIthirds01=.5 blackXRCCXCIthirds=0 treatment=1 treatXblack=0 treatXRCCpca3thirds=.5 treatXblackXRCCthirds=0 treatXCIthirds=1 treatXblackXCIthirds=0 treatXRCCXCIthirds=.5 treatXblackXRCCXCIthrds=.5) 
* now control low RCC hi CI
prvalue, x (blackwhite=0 RCCpca3thirds=0 CI01thirds=1 blackXRCCpca3thirds=0 blackXCIthirds=0 RCCXCIthirds01=0 blackXRCCXCIthirds=0 treatment=0 treatXblack=0 treatXRCCpca3thirds=0 treatXblackXRCCthirds=0 treatXCIthirds=0 treatXblackXCIthirds=0 treatXRCCXCIthirds=0 treatXblackXRCCXCIthrds=0) 
* ditto treatment group
prvalue, x (blackwhite=0 RCCpca3thirds=0 CI01thirds=1 blackXRCCpca3thirds=0 blackXCIthirds=0 RCCXCIthirds01=0 blackXRCCXCIthirds=0 treatment=1 treatXblack=0 treatXRCCpca3thirds=0 treatXblackXRCCthirds=0 treatXCIthirds=1 treatXblackXCIthirds=0 treatXRCCXCIthirds=0 treatXblackXRCCXCIthrds=0) 
* now control Hi RCC low CI
prvalue, x (blackwhite=0 RCCpca3thirds=1 CI01thirds=0 blackXRCCpca3thirds=0 blackXCIthirds=0 RCCXCIthirds01=0 blackXRCCXCIthirds=0 treatment=0 treatXblack=0 treatXRCCpca3thirds=0 treatXblackXRCCthirds=0 treatXCIthirds=0 treatXblackXCIthirds=0 treatXRCCXCIthirds=0 treatXblackXRCCXCIthrds=0) 
* ditto treatment group
prvalue, x (blackwhite=0 RCCpca3thirds=1 CI01thirds=0 blackXRCCpca3thirds=0 blackXCIthirds=0 RCCXCIthirds01=0 blackXRCCXCIthirds=0 treatment=1 treatXblack=0 treatXRCCpca3thirds=1 treatXblackXRCCthirds=0 treatXCIthirds=0 treatXblackXCIthirds=0 treatXRCCXCIthirds=0 treatXblackXRCCXCIthrds=0) 





